statestats

Generate bounded statistics based on a geojson file (currently using data/states.geojson, but any part of the globe will work).

Uses tile-reduce and osm-qa-tiles to calculate OSM editing statistics at the individual mapper level for each of the US States and Territories.

Number of buildings in OSM per state, normalized by population.

The final output (used to generate the above map) is states_with_stats_normalized.geojson. This file contains per state statistics in three ways: raw, normalized by population, or normalized by area.

Contents

The results folder contains the following folders:

folder	contents
csv	A CSV file per State/Territory containing per-mapper edit counts, such as colorado_mappers.csv
wordclouds	Wordclouds (images) visualizing the top 100 values for common keys, such as amenity, shop, and leisure. Calculated per tag, per State/Territory such as arkansas_wordcloud_leisure.png
json	Output from tile-reduce, counts for users (_users.json) and tag values (_values.json)
geojson	Per State/Territory geojson file with stats produced by tile-reduce.

Individual mapper CSVs, per State.

counted from all OSM users/objects (that are in osm-qa-tiles), including imports.

Here's an example of the colorado_mappers.csv file:

user	building	dry_cleaning	highway	ice_cream	laundry	total_objects
chachafish	82265	27	4418.956827547136	17	18	377082
Your Village Maps	23224	1	5618.477728813425	0	43	220505
SK53_bulk	0	0	115.33849548447466	0	0	191551
Skybunny	5	0	19.979800499649546	0	0	70022
aboges26	74	0	1627.6421876299278	0	0	68496
TheDutchMan13	3	0	21588.04711432218	0	0	66621
Mark Newnham	7267	0	11743.816325855196	0	0	66322
CornCO	7566	1	530.805211083113	0	0	65791
DavidJDBA	23682	0	11886.930341476647	0	0	64233

Running

A python script runs node index.js <place> for all of the features in data/states.geojson.

./run.sh 

This script is expecting latest.planet-compact.mbtiles in the parent directory.

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Wordcloud Examples

Colorado leisure top values

Hawaii leisure top values